An analytical model for multi-tier internet services and its applications
SIGMETRICS '05 Proceedings of the 2005 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Ensembles of Models for Automated Diagnosis of System Performance Problems
DSN '05 Proceedings of the 2005 International Conference on Dependable Systems and Networks
Advanced Message Queuing Protocol
IEEE Internet Computing
Building a Monitoring Infrastructure with Nagios
Building a Monitoring Infrastructure with Nagios
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NSDI'05 Proceedings of the 2nd conference on Symposium on Networked Systems Design & Implementation - Volume 2
A Regression-Based Analytic Model for Dynamic Resource Provisioning of Multi-Tier Applications
ICAC '07 Proceedings of the Fourth International Conference on Autonomic Computing
Agile dynamic provisioning of multi-tier Internet applications
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
1000 Islands: Integrated Capacity and Workload Management for the Next Generation Data Center
ICAC '08 Proceedings of the 2008 International Conference on Autonomic Computing
Benchmarking cloud serving systems with YCSB
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Probabilistic performance modeling of virtualized resource allocation
Proceedings of the 7th international conference on Autonomic computing
EC2 performance analysis for resource provisioning of service-oriented applications
ICSOC/ServiceWave'09 Proceedings of the 2009 international conference on Service-oriented computing
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While public cloud computing platforms have become popular in recent years, private clouds---operated by enterprises for their internal use---have also begun gaining traction. The configuration and continuous tuning of a private cloud to meet user demands is a complex task. While private cloud management frameworks provide a number of flexible configuration options for this purpose, they leave it to the administrator to determine how to best configure and tune the cloud platform for local needs. In this paper, we argue for an adaptive control plane for private clouds that simplifies the tasks of configuring and operating a private cloud such that each control plane service is adaptive to the workload seen due to end-user requests. We present a logistic regression model to automate the provisioning and dynamic reconfiguration of control plane services in a private cloud. We implement our approach for two control plane services---monitoring and messaging---for OpenStack-based private clouds. Our experimental results on a laboratory private cloud testbed and using public cloud workloads demonstrates the ability of our approach to provision and adapt such services from very small to very large private cloud configurations.